Sarma Dipjyoti, Nath Kaushik K, Biswas Sritam, Ahmed Gazi Ameen, Nath Pabitra
Applied Photonics and Nanophotonics Laboratory, Department of Physics, Tezpur University, Napaam 784028, Assam, India.
Optoelectronics and Photonics Research Laboratory, Tezpur University, Napaam 784028, Assam, India.
Spectrochim Acta A Mol Biomol Spectrosc. 2025 Feb 15;327:125417. doi: 10.1016/j.saa.2024.125417. Epub 2024 Nov 10.
Design of a sensitive, cost-effective SERS substrate is critical for probing analyte in trace concentration in real field environment. Present work reports the fabrication of an oxygen (O) plasma treated bimetallic nanofibers as a sensitive SERS platform. In contrast to the conventional nanofiber-based SERS platform, the proposed plasma-treated bimetallic nanofibers-based SERS platform offers high sensitivity and reproducibility characteristics. On top, the use of bimetallic nanoparticles provides a synergistic effect, contributing to both electromagnetic and chemical enhancement to SERS performance and the plasma treatment contributes to the controlled exposure of the embedded nanoparticles (NPs) to the analyte thereby enhancing the overall sensitivity of the proposed technique. With standard Raman active probe molecules - 1,2-bis(4-pyridyl) ethylene (BPE) and rhodamine-6G (R6G) the limit of detection (LOD) and the limit of quantification (LOQ) of the proposed sensing platform are estimated to be 3.8 nM and 11.6 nM respectively. The enhancement factor (EF) of the designed sensing platform is calculated to be ∼10 with a maximum signal variations of 5 %. The applicability of the designed SERS substrate has been realized through detection of two antibiotics - fluconazole (FLU) and lincomycin (LIN) widely used in poultry farms. Furthermore, a deep learning model - artificial neural network (ANN) has been implemented for effective classification of the analyte molecules from a mixed sample.
设计一种灵敏且经济高效的表面增强拉曼光谱（SERS）基底对于在实际现场环境中探测痕量浓度的分析物至关重要。目前的工作报道了一种经氧（O）等离子体处理的双金属纳米纤维作为灵敏的SERS平台的制备。与传统的基于纳米纤维的SERS平台相比，所提出的经等离子体处理的基于双金属纳米纤维的SERS平台具有高灵敏度和可重复性的特点。此外，双金属纳米颗粒的使用提供了协同效应，有助于表面增强拉曼光谱性能的电磁和化学增强，而等离子体处理有助于使嵌入的纳米颗粒（NPs）可控地暴露于分析物，从而提高了所提出技术的整体灵敏度。使用标准的拉曼活性探针分子——1,2-双（4-吡啶基）乙烯（BPE）和罗丹明-6G（R6G），所提出的传感平台的检测限（LOD）和定量限（LOQ）分别估计为3.8 nM和11.6 nM。所设计的传感平台的增强因子（EF）计算为~10，最大信号变化为5%。通过检测家禽养殖场广泛使用的两种抗生素——氟康唑（FLU）和林可霉素（LIN），实现了所设计的SERS基底的适用性。此外，还实施了一种深度学习模型——人工神经网络（ANN），用于对混合样品中的分析物分子进行有效分类。
